SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 4171–4180 of 4891 papers

TitleStatusHype
Multi-frequency calibration for DOA estimation with distributed sensors—0
Complete Dictionary Learning via _p-norm MaximizationCode1
Multi-objective beetle antennae search algorithm—0
Improving STDP-based Visual Feature Learning with Whitening—0
Asymptotic Linearity of Consumption Functions and Computational Efficiency—0
Transformer Hawkes ProcessCode1
Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic ProgrammingCode0
Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-ResolutionCode0
Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients—0
Gaussian Mixture Reduction with Composite Transportation DivergenceCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified